Cohort profile: Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) - an international consortium of prospective cohort studies with individual participant data on hip osteoarthritis

PURPOSE

Hip osteoarthritis (OA) is a major cause of pain and disability worldwide. Lack of effective therapies may reflect poor knowledge on its aetiology and risk factors, and result in the management of end-stage hip OA with costly joint replacement. The Worldwide Collaboration on OsteoArthritis prediCtion for the Hip (World COACH) consortium was established to pool and harmonise individual participant data from prospective cohort studies. The consortium aims to better understand determinants and risk factors for the development and progression of hip OA, to optimise and automate methods for (imaging) analysis, and to develop a personalised prediction model for hip OA.

PARTICIPANTS

World COACH aimed to include participants of prospective cohort studies with ≥200 participants, that have hip imaging data available from at least 2 time points at least 4 years apart. All individual participant data, including clinical data, imaging (data), biochemical markers, questionnaires and genetic data, were collected and pooled into a single, individual-level database.

FINDINGS TO DATE

World COACH currently consists of 9 cohorts, with 38 021 participants aged 18-80 years at baseline. Overall, 71% of the participants were women and mean baseline age was 65.3±8.6 years. Over 34 000 participants had baseline pelvic radiographs available, and over 22 000 had an additional pelvic radiograph after 8-12 years of follow-up. Even longer radiographic follow-up (15-25 years) is available for over 6000 of these participants.

FUTURE PLANS

The World COACH consortium offers unique opportunities for studies on the relationship between determinants/risk factors and the development or progression of hip OA, by using harmonised data on clinical findings, imaging, biomarkers, genetics and lifestyle. This provides a unique opportunity to develop a personalised hip OA risk prediction model and to optimise methods for imaging analysis of the hip.

Looking back on 30+ years of the Johnston County Osteoarthritis Project while looking forward with the Johnston County Health Study: A narrative review

Over the last 30 years, knowledge of the epidemiology of osteoarthritis (OA) has dramatically advanced, and Osteoarthritis and Cartilage has been on the forefront of disseminating research findings from large OA cohort studies, including the Johnston County OA Project (JoCoOA). The JoCoOA is a population-based, prospective longitudinal cohort that began roughly 30 years ago with a key focus on understanding prevalence, incidence, and progression of OA, as well as its risk factors, in a predominantly rural population of Black and White adults 45+ years old in a county in the southeastern United States. Selected OA results that will be discussed in this review include racial differences, lifetime risk, biomarkers, mortality, and OA risk factors. The new Johnston County Health Study will also be introduced. This new cohort study of OA and comorbid conditions builds upon current OA knowledge and JoCoOA infrastructure and is designed to reflect changes in demographics and urbanization in the county and the region.

Serum proteomic biomarkers diagnostic of knee osteoarthritis

OBJECTIVE

To better understand the pathogenesis of knee osteoarthritis (OA) through identification of serum diagnostics.

DESIGN

We conducted multiple reaction monitoring mass spectrometry analysis of 107 peptides in baseline sera of two cohorts: the Foundation for National Institutes of Health (NIH) (n = 596 Kellgren-Lawrence (KL) grade 1-3 knee OA participants); and the Johnston County Osteoarthritis Project (n = 127 multi-joint controls free of radiographic OA of the hands, hips, knees (bilateral KL=0), and spine). Data were split into (70%) training and (30%) testing sets. Diagnostic peptide and clinical data predictors were selected by random forest (RF); selection was based on association (p < 0.05) with OA status in multivariable logistic regression models. Model performance was based on area under the curve (AUC) of receiver operating characteristic (ROC) and precision-recall (PR) curves.

RESULTS

RF selected 23 peptides (19 proteins) and body mass index (BMI) as diagnostic of OA. BMI weakly diagnosed OA (ROC-AUC 0.57, PR-AUC 0.812) and only symptomatic OA cases. ACTG was the strongest univariable predictor (ROC-AUC 0.705, PR-AUC 0.897). The final model (8 serum peptides) was highly diagnostic (ROC-AUC 0.833, 95% confidence interval [CI] 0.751, 0.905; PR-AUC 0.929, 95% CI 0.876, 0.973) in the testing set and equally diagnostic of non-symptomatic and symptomatic cases (AUCs 0.830-0.835), and not significantly improved with addition of BMI. The STRING database predicted multiple high confidence interactions of the 19 diagnostic OA proteins.

CONCLUSIONS

No more than 8 serum protein biomarkers were required to discriminate knee OA from non-OA. These biomarkers lend strong support to the involvement and cross-talk of complement and coagulation pathways in the development of OA.

Multiple joint osteoarthritis (MJOA): What's in a name?

OBJECTIVE

To summarize the current state of the literature regarding multi-joint osteoarthritis (MJOA) and discuss important future directions.

DESIGN

A narrative review of the author's work and other key references on this topic with a focus on the Johnston County studies, definitions of MJOA and their impact, multi-site pain in osteoarthritis (OA), genetics and biomarkers in MJOA, and perspectives on future work.

RESULTS

MJOA is variably defined and lacks a clear consensus definition, making comprehensive study challenging. Involvement of both symptoms and structural changes of OA in multiple joints in an individual is common, but patterns vary by sex, race/ethnicity, and other factors. Outcomes (e.g., general health, function, falls, mortality) are negatively impacted by a greater whole-body OA burden. Recent genetic and biomarker studies including whole-body OA assessments have begun to shed some light on potentially unique factors in the MJOA population.

CONCLUSIONS

Consideration of MJOA is essential for ongoing study of OA phenotypes, epidemiology, risk factors, genetics, biomarkers, and outcomes, to fully understand and eventually limit the negative impact of OA burden on health.

The Critical Role of Physical Activity and Weight Management in Knee and Hip Osteoarthritis: A Narrative Review

Physical activity (PA) and weight management are critical components of an effective knee and hip osteoarthritis (OA) management plan, yet most people with OA remain insufficiently active and/or overweight. Clinicians and their care teams play an important role in educating patients with OA about PA and weight management, eliciting patient motivation to engage in these strategies, and referring patients to appropriate self-management interventions. The purpose of this review is to educate clinicians about the current public health and clinical OA guidelines for PA and weight management and highlight a variety of evidence-based self-management interventions available in community and clinical settings and online.

Epidemiology of osteoarthritis: literature update 2022-2023

PURPOSE OF REVIEW

This review highlights recently published studies on osteoarthritis (OA) epidemiology, including topics related to understudied populations and joints, imaging, and advancements in artificial intelligence (AI) methods.

RECENT FINDINGS

Contemporary research has improved our understanding of the burden of OA in typically understudied regions, including ethnic and racial minorities in high-income countries, the Middle East and North Africa (MENA) and Latin America. Efforts have also been made to explore the burden and risk factors in OA in previously understudied joints, such as the hand, foot, and ankle. Advancements in OA imaging techniques have occurred alongside the developments of AI methods aiming to predict disease phenotypes, progression, and outcomes.

SUMMARY

Continuing efforts to expand our knowledge around OA in understudied populations will allow for the creation of targeted and specific interventions and inform policy changes aimed at reducing disease burden in these groups. The burden and disability associated with OA is notable in understudied joints, warranting further research efforts that may lead to effective therapeutic options. AI methods show promising results of predicting OA phenotypes and progression, which also may encourage the creation of targeted disease modifying OA drugs (DMOADs).

Tick-Borne Disease Infections and Chronic Musculoskeletal Pain

Importance

Tick-borne diseases (TBDs) other than Lyme disease, such as spotted fever group rickettsiosis, ehrlichiosis, and galactose-α-1,3-galactose (α-gal) syndrome, are an emerging public health issue. Long-term sequelae secondary to Ehrlichia or Rickettsia infection are uncommon; however, musculoskeletal symptoms are often attributed to prior tick exposure.

Objective

To evaluate the potential associations between prior exposure to TBDs and musculoskeletal symptoms, including radiographic osteoarthritis.

Design, Setting, and Participants

This cross-sectional study analyzed serum samples from the fourth visit (2017-2018) of the Johnston County Osteoarthritis (JoCo OA) project, an ongoing longitudinal, population-based study in Johnston County, North Carolina. Biospecimen testing and analysis were performed between May 2022 and November 2023. Participants in the JoCo OA project are noninstitutionalized White and Black Johnston County residents 45 years or older.

Main Outcome and Measures

The primary outcome was seropositivity with Ehrlichia IgG, Rickettsia IgG, and/or α-gal IgE and musculoskeletal symptoms. Secondary outcomes included risk factors associated with elevated α-gal IgE and weighted population point prevalence rates. Participants completed questionnaires, underwent physical assessments, and provided biospecimens for serological testing. Multivariable models were used to estimate associations of interest.

Results

Of the 605 participants who completed the fourth visit of the JoCo OA project, 488 (80.7%) had serum samples available for testing. The 488 participants had a median (IQR) age of 72 (68-78) years and included 336 females (68.9%) and 161 Black (33.0%) and 327 White (67.0%) individuals. The overall weighted point prevalence was 8.6% (95% CI, 5.9%-11.3%) for Ehrlichia IgG, 17.1% (95% CI, 12.6%-21.5%) for Rickettsia IgG, and 19.6% (95% CI, 15.3%-23.8%) for α-gal IgE level greater than 0.1 IU/mL. Only α-gal IgE was associated with knee pain, aching or stiffness (mean ratio, 1.30; 95% CI, 1.09-1.56). Antibodies to Rickettsia, Ehrlichia, and α-gal were not associated with symptomatic radiographic knee osteoarthritis. Male sex (odds ratio [OR], 2.63; 95% CI, 1.55-4.47), current smoker status (OR, 3.55; 95% CI, 1.38-9.18), and an attached tick bite in the past 5 years (OR, 3.99; 95% CI, 2.22-7.15) were all risk factors that were associated with α-gal IgE level greater than 0.1 IU/mL. Despite only 84 individuals (17.2%) recalling a tick bite in the past 5 years, 178 (36.5%) had evidence of prior tick-borne exposure, suggesting frequent human-tick interactions.

Conclusions and Relevance

Results of this cross-sectional study indicate no association between Ehrlichia or Rickettsia seropositivity and chronic musculoskeletal symptoms or osteoarthritis. Further investigation is needed into the pathogenesis of α-gal syndrome and interventions to reduce human-tick interactions.

Arthritis Foundation/HSS Workshop on Hip Osteoarthritis, Part 1: Epidemiology, Early Development, and Cohorts From Around the World

Far more publications are available for osteoarthritis of the knee than of the hip. Recognizing this research gap, the Arthritis Foundation, in partnership with the Hospital for Special Surgery, convened an in-person meeting of thought leaders to review the state of the science of and clinical approaches to hip osteoarthritis. This article summarizes the recommendations and clinical research gaps gleaned from 5 presentations given in the "how hip osteoarthritis begins" session of the 2023 Hip Osteoarthritis Clinical Studies Conference, which took place on February 17 and 18, 2023, in New York City.

Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes

PURPOSE OF REVIEW

Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and patients in decision making, based on machine-learned evidence, and (2) improve our understanding of pathophysiology and mechanisms underlying OA, providing new insights into disease management and prevention. The purpose of this review is to improve the ability of clinicians and OA researchers to understand the strengths and limitations of AI/ML methods in applications to OA research.

RECENT FINDINGS

AI/ML can assist clinicians by prediction of OA incidence and progression and by providing tailored personalized treatment. These methods allow using multidimensional multi-source data to understand the nature of OA, to identify different OA phenotypes, and for biomarker discovery. We described the recent implementations of AI/ML in OA research and highlighted potential future directions and associated challenges.

Precision Medicine-Based Machine Learning Analyses to Explore Optimal Exercise Therapies for Individuals With Knee Osteoarthritis: Random Forest-Informed Tree-Based Learning

OBJECTIVE

We applied a precision medicine-based machine learning approach to discover underlying patient characteristics associated with differential improvement in knee osteoarthritis symptoms following standard physical therapy (PT), internet-based exercise training (IBET), and a usual care/wait list control condition.

METHODS

Participants (n = 303) were from the Physical Therapy vs Internet-Based Training for Patients with Knee Osteoarthritis trial. The primary outcome was the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score at 12-month follow-up. Random forest-informed tree-based learning was applied to identify patient characteristics that were critical to improving outcomes, and patients with those features were grouped.

RESULTS

Age, BMI, and Brief Fear of Movement (BFOM) score, all at baseline, were identified as characteristics that effectively divided participants, creating 6 subgroups. Assigning treatments according to these models, compared to assigning a single best treatment to all patients, resulted in greater improvements of the average WOMAC at 12 months (P = 0.01). Key patterns were that IBET was the optimal treatment for patients of younger age and low BFOM, whereas PT was the optimal treatment for patients of older age, high BFOM, and BMI (kg/m2) between 26.3 and 37.2.

CONCLUSION

These results suggest that easily assessed patient characteristics including age, fear of movement, and BMI could be used to guide patients toward either home-based exercise or PT, though additional studies are needed to confirm these findings. (ClinicalTrials.gov: NCT02312713).

Features of Knee and Multijoint Osteoarthritis by Sex and Race and Ethnicity: A Preliminary Analysis in the Johnston County Health Study

OBJECTIVE

To evaluate knee osteoarthritis (KOA) and multijoint osteoarthritis (MJOA), and to compare features by sex and race and ethnicity in a population-based cohort.

METHODS

Participants (n = 544) enrolled in the Johnston County Health Study (JoCoHS) as of January 2023 were categorized by radiographic and symptomatic KOA and MJOA phenotypes, and frequencies were compared by sex and race and ethnicity. Symptoms were assessed according to the Knee Injury and Osteoarthritis Outcome Score (KOOS) and pain, aching, and stiffness (PAS) scores at various joints. Models produced estimates (odds ratio [OR] or mean ratios [MR] and 95% CI) adjusted for age, BMI (kg/m2), and education.

RESULTS

Men had twice the odds of having MJOA-6 (≥ 3 lower extremity joints affected); there were no significant differences in MJOA phenotypes by race and ethnicity. Women had 50% higher odds of having KOA or having various features of KOA. Women reported significantly worse KOOS Symptoms scores (MR 1.25). Black participants had higher odds of more severe KOA (OR 1.47), subchondral sclerosis (OR 2.06), and medial tibial osteophytes (OR 1.50). Black participants reported worse KOOS Symptoms than White participants (MR 1.18). Although not statistically significant, Hispanic participants (vs non-Hispanic participants) appeared to have lower odds of radiographic changes but reported worse symptoms.

CONCLUSION

Preliminary findings in the diverse JoCoHS cohort suggest more lower extremity- predominant MJOA in men compared to women. Women and Black participants had more KOA features and more severe symptoms. Hispanic participants appear to have higher pain and symptoms scores despite having fewer structural changes. Studies in diverse populations are needed to understand the burden of OA.

Charting Aging Trajectories of Knee Cartilage Thickness for Early Osteoarthritis Risk Prediction: An MRI Study from the Osteoarthritis Initiative Cohort

Knee osteoarthritis (OA), a prevalent joint disease in the U.S., poses challenges in terms of predicting of its early progression. Although high-resolution knee magnetic resonance imaging (MRI) facilitates more precise OA diagnosis, the heterogeneous and multifactorial aspects of OA pathology remain significant obstacles for prognosis. MRI-based scoring systems, while standardizing OA assessment, are both time-consuming and labor-intensive. Current AI technologies facilitate knee OA risk scoring and progression prediction, but these often focus on the symptomatic phase of OA, bypassing initial-stage OA prediction. Moreover, their reliance on complex algorithms can hinder clinical interpretation. To this end, we make this effort to construct a computationally efficient, easily-interpretable, and state-of-the-art approach aiding in the radiographic OA (rOA) auto-classification and prediction of the incidence and progression, by contrasting an individual's cartilage thickness with a similar demographic in the rOA-free cohort. To better visualize, we have developed the toolset for both prediction and local visualization. A movie demonstrating different subtypes of dynamic changes in local centile scores during rOA progression is available at https://tli3.github.io/KneeOA/. Specifically, we constructed age-BMI-dependent reference charts for knee OA cartilage thickness, based on MRI scans from 957 radiographic OA (rOA)-free individuals from the Osteoarthritis Initiative cohort. Then we extracted local and global centiles by contrasting an individual's cartilage thickness to the rOA-free cohort with a similar age and BMI. Using traditional boosting approaches with our centile-based features, we obtain rOA classification of KLG ≤ 1 versus KLG = 2 (AUC = 0.95, F1 = 0.89), KLG ≤ 1 versus KLG ≥ 2 (AUC = 0.90, F1 = 0.82) and prediction of KLG2 progression (AUC = 0.98, F1 = 0.94), rOA incidence (KLG increasing from < 2 to ≥ 2; AUC = 0.81, F1 = 0.69) and rOA initial transition (KLG from 0 to 1; AUC = 0.64, F1 = 0.65) within a future 48-month period. Such performance in classifying KLG ≥ 2 matches that of deep learning methods in recent literature. Furthermore, its clinical interpretation suggests that cartilage changes, such as thickening in lateral femoral and anterior femoral regions and thinning in lateral tibial regions, may serve as indicators for prediction of rOA incidence and early progression. Meanwhile, cartilage thickening in the posterior medial and posterior lateral femoral regions, coupled with a reduction in the central medial femoral region, may signify initial phases of rOA transition.

Association of Foot Symptoms With Decreased Time to All-Cause Mortality: The Johnston County Osteoarthritis Project

OBJECTIVE

Adults with foot symptoms (ie, pain, aching, or stiffness) may be at increased risk of reduced time to all-cause mortality. The purpose of this study was to evaluate whether foot symptoms are independently associated with all-cause mortality in older adults.

METHODS

We analyzed longitudinal data from 2613 participants from the Johnston County Osteoarthritis Project, a longitudinal population-based cohort of adults 45 years of age and older. Participants completed questionnaires at baseline to determine presence of foot symptoms and covariable status. Baseline walking speed was measured via an 8-foot walk test. To examine the association of foot symptoms with time to mortality, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox regression models, adjusted for potential confounders.

RESULTS

We observed 813 deaths over 4 to 14.5 years of follow-up. At baseline, 37% of participants had foot symptoms, mean age was 63 years, mean body mass index was approximately 31 kg/m2 , 65% were women, and 33% were Black. Moderate to severe foot symptoms were associated with reduced time to mortality after adjustment for demographics, comorbidities, physical activity, and knee and hip symptoms (HR = 1.30, 95% CI 1.09-1.54). Importantly, this association was not modified by walking speed or diabetes.

CONCLUSION

Individuals with foot symptoms had an increased hazard of all-cause mortality compared with those with no foot symptoms. These effects were independent of key confounders and were not moderated by walking speed. Effective interventions to identify and manage at least moderate foot symptoms may reduce the risk of decreased time to mortality.

Patterns of variation among baseline femoral and tibial cartilage thickness and clinical features: Data from the osteoarthritis initiative

Objective

To employ novel methodologies to identify phenotypes in knee OA based on variation among three baseline data blocks: 1) femoral cartilage thickness, 2) tibial cartilage thickness, and 3) participant characteristics and clinical features.

Methods

Baseline data were from 3321 Osteoarthritis Initiative (OAI) participants with available cartilage thickness maps (6265 knees) and 77 clinical features. Cartilage maps were obtained from 3D DESS MR images using a deep-learning based segmentation approach and an atlas-based analysis developed by our group. Angle-based Joint and Individual Variation Explained (AJIVE) was used to capture and quantify variation, both shared among multiple data blocks and individual to each block, and to determine statistical significance.

Results

Three major modes of variation were shared across the three data blocks. Mode 1 reflected overall thicker cartilage among men, those with higher education, and greater knee forces; Mode 2 showed associations between worsening Kellgren-Lawrence Grade, medial cartilage thinning, and worsening symptoms; and Mode 3 contrasted lateral and medial-predominant cartilage loss associated with BMI and malalignment. Each data block also demonstrated individual, independent modes of variation consistent with the known discordance between symptoms and structure in knee OA and reflecting the importance of features such as physical function, symptoms, and comorbid conditions independent of structural damage.

Conclusions

This exploratory analysis, combining the rich OAI dataset with novel methods for determining and visualizing cartilage thickness, reinforces known associations in knee OA while providing insights into the potential for data integration in knee OA phenotyping.

Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project

OBJECTIVE

The lack of accurate biomarkers to predict knee osteoarthritis (OA) progression is a key unmet need in OA clinical research. The objective of this study was to develop baseline peripheral blood epigenetic biomarker models to predict knee OA progression.

METHODS

Genome-wide buffy coat DNA methylation patterns from 554 individuals from the Osteoarthritis Biomarkers Consortium (OABC) were determined using Illumina Infinium MethylationEPIC 850K arrays. Data were divided into model development and validation sets, and machine learning models were trained to classify future OA progression by knee pain, radiographic imaging, knee pain plus radiographic imaging, and any progression (pain, radiographic, or both). Parsimonious models using the top 13 CpG sites most frequently selected during development were tested on independent samples from participants in the Johnston County Osteoarthritis (JoCo OA) Project (n = 128) and a previously published Osteoarthritis Initiative (OAI) data set (n = 55).

RESULTS

Full models accurately classified future radiographic-only progression (mean ± SEM accuracy 87 ± 0.8%, area under the curve [AUC] 0.94 ± 0.004), pain-only progression (accuracy 89 ± 0.9%, AUC 0.97 ± 0.004), pain plus radiographic progression (accuracy 72 ± 0.7%, AUC 0.79 ± 0.006), and any progression (accuracy 78 ± 0.4%, AUC 0.86 ± 0.004). Pain-only and radiographic-only progressors were not distinguishable (mean ± SEM accuracy 58 ± 1%, AUC 0.62 ± 0.001). Parsimonious models showed similar performance and accurately classified future radiographic progressors in the OABC cohort and in both validation cohorts (mean ± SEM accuracy 80 ± 0.3%, AUC 0.88 ± 0.003 [using JoCo OA Project data], accuracy 80 ± 0.8%, AUC 0.89 ± 0.002 [using previous OAI data]).

CONCLUSION

Our data suggest that pain and structural progression share similar early systemic immune epigenotypes. Further studies should focus on evaluating the pathophysiologic consequences of differential DNA methylation and peripheral blood cell epigenotypes in individuals with knee OA.

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

BACKGROUND

Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery.

RESULTS

To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3-5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism.

CONCLUSIONS

Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.

Association of plasma microbial composition with a leaky gut in obesity-related osteoarthritis: An exploratory study

Objective

To examine the plasma microbiome for differences between obese individuals with and without osteoarthritis (OA) and its association with serum lipopolysaccharide (LPS).

Design

Blood samples from 70 participants with body mass index (BMI) ​≥ ​30kg/m2 and age ≥55 years, with (cases) or without (controls) hand plus knee OA, were analyzed for serum LPS and composition of the plasma microbiome. The Dirichlet-multinominal recursive partitioning model (DM-RPart) was applied to microbiome compositional data to test the hypothesis that LPS levels distinguish plasma microbiome, accounting for BMI and age.

Results

No significant differences in alpha diversity, or compositional differences between groups at the genus level, were seen between cases and controls (p ​= ​0.11). β-Diversity was significantly associated with serum LPS levels (p ​= ​0.01). DM-RPart resulted in an optimal tree with 3 divisions: 1) based on age (split at 69 years); 2) those older than 69 were split based on BMI; 3) those with BMI <39 ​kg/m2 were split based on LPS level (at 65 EU/ml). This resulted in 4 groups (nodes 2, and 5-7). Participants in node 2 were younger and the majority had no or mild OA. Those in nodes 5 and 6 were comparable in age and BMI but node 6 had higher LPS and more severe OA. Individuals in node 7 were older, had higher BMI, and the most severe OA.

Conclusions

Our results suggest a relationship between serum LPS and the plasma microbiome in a subgroup of obese individuals with hand plus knee OA that could reflect differences in intestinal permeability.

Associations Between Baseline and Longitudinal Semiautomated Quantitative Joint Space Width at the Hip and Incident Hip Osteoarthritis: Data From a Community-Based Cohort

OBJECTIVE

To evaluate quantitative joint space width (JSW) at 10-, 30-, and 50-degree locations in relation to incident radiographic and symptomatic hip osteoarthritis (HOA) in a community-based cohort.

METHODS

Data were from Johnston County OA Project participants with supine hip radiographs at each of 4 time points; all had Kellgren/Lawrence (K/L) grades and quantitative JSW. We assessed covariates (age, race, height, weight, body mass index [BMI]) associated with quantitative JSW and hip-level associations between quantitative JSW and HOA over time using sex-stratified and multivariable-adjusted linear mixed models. A cluster analysis with logistic regression estimated associations between quantitative JSW trajectory groups and incident radiographic HOA and symptomatic HOA.

RESULTS

At baseline, 397 participants (784 hips, 41% men, 24% Black, mean age 57 years) had a mean BMI of 29 kg/m2 . Over a mean of 18 years, 20% and 12% developed incident K/L grade-defined radiographic HOA or symptomatic HOA, respectively. Quantitative JSW was more sensitive to changes over time at 50 degrees. Values were stable among men but declined over time in women. Heavier women lost more quantitative JSW; changes in quantitative JSW were not significantly associated with race, education, or injury in women or men. In women only, loss of quantitative JSW over time was associated with 2-3 times higher odds of radiographic HOA and symptomatic HOA; among women and men, narrower baseline quantitative JSW was associated with these outcomes.

CONCLUSION

Hip quantitative JSW demonstrates marked differences in respect to sex, with significant loss over time only in women. Loss of quantitative JSW over time in women and narrower baseline quantitative JSW in men and women were associated with incident radiographic HOA and symptomatic HOA.

Narrative Review of Machine Learning in Rheumatic and Musculoskeletal Diseases for Clinicians and Researchers: Biases, Goals, and Future Directions

There has been rapid growth in the use of artificial intelligence (AI) analytics in medicine in recent years, including in rheumatic and musculoskeletal diseases (RMDs). Such methods represent a challenge to clinicians, patients, and researchers, given the "black box" nature of most algorithms, the unfamiliarity of the terms, and the lack of awareness of potential issues around these analyses. Therefore, this review aims to introduce this subject area in a way that is relevant and meaningful to clinicians and researchers. We hope to provide some insights into relevant strengths and limitations, reporting guidelines, as well as recent examples of such analyses in key areas, with a focus on lessons learned and future directions in diagnosis, phenotyping, prognosis, and precision medicine in RMDs.

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Association of Biomarkers with Individual and Multiple Body Sites of Pain: The Johnston County Osteoarthritis Project

Introduction

Biochemical biomarkers may provide insight into musculoskeletal pain reported at individual or multiple body sites. The purpose of this study was to determine if biomarkers or pressure-pain threshold (PPT) were associated with individual or multiple sites of pain.

Methods

This cross-sectional analysis included 689 community-based participants. Self-reported symptoms (ie, pain, aching, or stiffness) were ascertained about the neck, upper back/thoracic, low back, shoulders, elbows, wrist, hands, hips, knees, ankles, and feet. Measured analytes included CXCL-6, RANTES, HA, IL-6, BDNF, OPG and NPY. A standard dolorimeter measured PPT. Logistic regression was used determine the association between biomarkers and PPT with individual and summed sites of pain.

Results

Increased IL-6 and HA were associated with knee pain (OR=1.30, 95% CI 1.03, 1.64) and (OR=1.32, 95% CI 1.01, 1.73) respectively; HA was also associated with elbow/wrist/hand pain (OR=1.60, 95% CI 1.22, 2.09). Those with increased NPY levels were less likely to have shoulder pain (OR=0.56, 95% CI 0.33, 0.93). Biomarkers HA (OR=1.50, 95% CI 1.07, 2.10), OPG (OR=1.74, 95% CI 1.00, 3.03), CXCL-6 (OR=1.75, 95% CI 1.02, 3.01) and decreased PPT (OR=3.97, 95% CI 2.22, 7.12) were associated with multiple compared to no sites of pain. Biomarker HA (OR=1.57, 95% CI 1.06, 2.32) and decreased PPT (OR=3.53, 95% CI 1.81, 6.88) were associated with multiple compared to a single site of pain.

Conclusion

Biomarkers of inflammation (HA, OPG, IL-6 and CXCL-6), pain (NPY) and PPT may help to understand the etiology of single and multiple pain sites.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

Osteoarthritis Treatment Guidelines from Six Professional Societies

Despite the high prevalence and burden of osteoarthritis (OA) worldwide, management of OA continues to primarily focus on symptom management due to the lack of approved pharmacologic agents that halt disease progression. Recent recommendations from 6 professional societies support the importance of education, self-management approaches, weight loss, and physical modalities in managing OA. These recent guidelines also highlight the paucity of effective and safe treatment options, with recommendations against ineffective therapies outnumbering those for effective ones. NSAIDs, oral and topical, remain the primary recommended pharmacologic management option for OA.

Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative

Objective

To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time.

Methods

Data from the baseline Osteoarthritis Initiative (OAI) visit were cleaned, transformed, and standardized as indicated (leaving 6461 knees with 86 features). Biclustering produced submatrices of the overall data matrix, representing similar observations across a subset of variables. Statistical validation was determined using the novel SigClust procedure. After identifying biclusters, relationships with key outcome measures were assessed, including progression of radiographic KOA, total knee arthroplasty, loss of joint space width, and worsening Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, over 96 months of follow-up.

Results

The final analytic set included 6461 knees from 3330 individuals (mean age 61 years, mean body mass index 28 kg/m², 57% women and 86% White). We identified 6 mutually exclusive biclusters characterized by different feature profiles at baseline, particularly related to symptoms and function. Biclusters represented overall better (#1), similar (#2, 3, 6), and poorer (#4, 5) prognosis compared to the overall cohort of knees, respectively. In general, knees in biclusters #4 and 5 had more structural progression (based on Kellgren-Lawrence grade, total knee arthroplasty, and loss of joint space width) but tended to have an improvement in WOMAC pain scores over time. In contrast, knees in bicluster #1 had less incident and progressive KOA, fewer total knee arthroplasties, less loss of joint space width, and stable pain scores compared with the overall cohort.

Significance

We identified six biclusters within the baseline OAI dataset which have varying relationships with key outcomes in KOA. Such biclusters represent potential phenotypes within the larger cohort and may suggest subgroups at greater or lesser risk of progression over time.

Recreational Physical Activity and Risk of Incident Knee Osteoarthritis: An International Meta-Analysis of Individual Participant-Level Data

OBJECTIVE

The effect of physical activity on the risk of developing knee osteoarthritis (OA) is unclear. We undertook this study to examine the relationship between recreational physical activity and incident knee OA outcomes using comparable physical activity and OA definitions.

METHODS

Data were acquired from 6 global, community-based cohorts of participants with and those without knee OA. Eligible participants had no evidence of knee OA or rheumatoid arthritis at baseline. Participants were followed up for 5-12 years for incident outcomes including the following: 1) radiographic knee OA (Kellgren-Lawrence [K/L] grade ≥2), 2) painful radiographic knee OA (radiographic OA with knee pain), and 3) OA-related knee pain. Self-reported recreational physical activity included sports and walking/cycling activities and was quantified at baseline as metabolic equivalents of task (METs) in days per week. Risk ratios (RRs) were calculated and pooled using individual participant data meta-analysis. Secondary analysis assessed the association between physical activity, defined as time (hours per week) spent in recreational physical activity and incident knee OA outcomes.

RESULTS

Based on a total of 5,065 participants, pooled RR estimates for the association of MET days per week with painful radiographic OA (RR 1.02 [95% confidence interval (95% CI) 0.93-1.12]), radiographic OA (RR 1.00 [95% CI 0.94-1.07]), and OA-related knee pain (RR 1.00 [95% CI 0.96-1.04]) were not significant. Similarly, the analysis of hours per week spent in physical activity also showed no significant associations with all outcomes.

CONCLUSION

Our findings suggest that whole-body, physiologic energy expenditure during recreational activities and time spent in physical activity were not associated with incident knee OA outcomes.

Association of Increased Serum Lipopolysaccharide, But Not Microbial Dysbiosis, With Obesity-Related Osteoarthritis

OBJECTIVE

To test the hypothesis that an altered gut microbiota (dysbiosis) plays a role in obesity-associated osteoarthritis (OA).

METHODS

Stool and blood samples were collected from 92 participants with a body mass index (BMI) ≥30 kg/m² , recruited from the Johnston County Osteoarthritis Project. OA patients (n = 50) had hand and knee OA (Kellgren/Lawrence [K/L] grade ≥2 or arthroplasty). Controls (n = 42) had no hand OA and a K/L grade of 0-1 for the knees. Compositional analysis of stool samples was carried out by 16S ribosomal RNA amplicon sequencing. Alpha- and beta-diversity and differences in taxa relative abundances were determined. Blood samples were used for multiplex cytokine analysis and measures of lipopolysaccharide (LPS) and LPS binding protein. Germ-free mice were gavaged with patient- or control-pooled fecal samples and fed a 40% fat, high-sucrose diet for 40 weeks. Knee OA was evaluated histologically.

RESULTS

On average, OA patients were slightly older than the controls, consisted of more women, and had a higher mean BMI, higher mean Western Ontario and McMaster Universities Osteoarthritis Index pain score, and higher mean K/L grade. There were no significant differences in α- or β-diversity or genus level composition between patients and controls. Patients had higher plasma levels of osteopontin (P = 0.01) and serum LPS (P < 0.0001) compared to controls. Mice transplanted with patient or control microbiota exhibited a significant difference in α-diversity (P = 0.02) and β-diversity, but no differences in OA severity were observed.

CONCLUSION

The lack of differences in the gut microbiota, but increased serum LPS levels, suggest the possibility that increased intestinal permeability allowing for greater absorption of LPS, rather than a dysbiotic microbiota, may contribute to the development of OA associated with obesity.

Developing a Primary Care-Focused Intervention to Engage Patients With Osteoarthritis in Physical Activity: A Stakeholder Engagement Qualitative Study

Physical activity (PA) is important for managing osteoarthritis (OA), but many patients are inactive. Research is needed on strategies to leverage clinical encounters to engage patients in PA. Guided by the socioecological model of health behavior, this study aimed to engage stakeholders in the process of refining an Osteoarthritis Physical Activity Care Pathway (OA-PCP). Six focus groups and seven individual interviews were conducted with key stakeholders. Focus groups were specific to stakeholder roles and included patients with OA, support partners, and clinic personnel (n = 6 focus groups). Interview participants were local and national PA program representatives (n = 7 interviews). Data were analyzed by thematic analysis. Themes identified in the data included ways the OA-PCP can help patients with OA address challenges to PA engagement, strategies for connecting patients with PA resources, methods for implementing OA-PCP into clinical settings and potential use of PA trackers in the OA-PCP program. Stakeholders' comments were summarized into key recommendations for OA-PCP. Some recommendations reinforced and led to refinements in planned aspects of OA-PCP, including tailoring to individual patients, involvement of a support partner, and addressing pain with PA. Other recommendations resulted in larger changes for OA-PCP, including the addition of three email- or mail-based contacts and not requiring use of a PA tracker. The refined OA-PCP program is being evaluated in an exploratory trial, with the ultimate goal of establishing a PA program for OA that can be successfully implemented in clinical settings.

Fecal metabolomics reveals products of dysregulated proteolysis and altered microbial metabolism in obesity-related osteoarthritis

OBJECTIVE

The objective of this exploratory study was to determine if perturbations in gut microbial composition and the gut metabolome could be linked to individuals with obesity and osteoarthritis (OA).

METHODS

Fecal samples were collected from obese individuals diagnosed with radiographic hand plus knee OA (n = 59), defined as involvement of at least 3 joints across both hands, and a Kellgren-Lawrence (KL) grade 2-4 (or total knee replacement) in at least one knee. Controls (n = 33) were without hand OA and with KL grade 0-1 knees. Fecal metabolomes were analyzed by a UHPLC/Q Exactive HFx mass spectrometer. Microbiome composition was determined in fecal samples by 16 S ribosomal RNA amplicon sequencing (rRNA-seq). Stepwise logistic regression models were built to determine microbiome and/or metabolic characteristics of OA.

RESULTS

Untargeted metabolomics analysis indicated that OA cases had significantly higher levels of di- and tripeptides and significant perturbations in microbial metabolites including propionic acid, indoles, and other tryptophan metabolites. Pathway analysis revealed several significantly perturbed pathways associated with OA including leukotriene metabolism, amino acid metabolism and fatty acid utilization. Logistic regression models selected metabolites associated with the gut microbiota and leaky gut syndrome as significant predictors of OA status, particularly when combined with the rRNA-seq data.

CONCLUSIONS

Adults with obesity and knee plus hand OA have distinct fecal metabolomes characterized by increased products of proteolysis, perturbations in leukotriene metabolism, and changes in microbial metabolites compared with controls. These metabolic perturbations indicate a possible role of dysregulated proteolysis in OA.

The power of genetic diversity in genome-wide association studies of lipids

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

Engagement between patients with obesity and osteoarthritis and primary care physicians: a cross-sectional survey

PURPOSE OF THE STUDY

Obesity is a major risk factor for development and worsening of osteoarthritis (OA). Managing obesity with effective weight loss strategies can improve patients' OA symptoms, functionality, and quality of life. However, little is known about the clinical journey of patients with both OA and obesity. This study aimed to map the medical journey of patients with OA and obesity by characterizing the roles of health care providers, influential factors, and how treatment decisions are made.

STUDY DESIGN

A cross-sectional study was completed with 304 patients diagnosed with OA and a body mass index (BMI) of ≥30 kg/m² and 101 primary care physicians (PCPs) treating patients who have OA and obesity.

RESULTS

Patients with OA and obesity self-manage their OA for an average of five years before seeking care from a healthcare provider, typically a PCP. Upon diagnosis, OA treatments were discussed; many (61%) patients reported also discussing weight/weight management. Despite most (74%) patients being at least somewhat interested in anti-obesity medication, few (13%) discussed this with their PCP. Few (12%) physicians think their patients are motivated to lose weight, but almost all (90%) patients have/are currently trying to lose weight. Another barrier to effective obesity management in patients with OA is the low utilization of clinical guidelines for OA and obesity management by PCPs.

CONCLUSIONS

As the care coordinator of patients with OA and obesity, PCPs have a key role in supporting their patients in the treatment journey; obesity management guidelines can be valuable resources.

High-Intensity Interval Training for Knee Osteoarthritis: A Pilot Study

OBJECTIVE

To assess the feasibility and changes in outcomes of a 12-week high-intensity interval training (HIIT) program in individuals with symptomatic knee osteoarthritis (OA).

METHODS

The single-arm trial included 29 participants (mean ± SD age 63 ± 7 years; 66% women; 66% obese). Measures of participant flow, adherence, and tolerability were collected. Pain, function, and balance were assessed at baseline, 6 weeks, and 12 weeks using the Western Ontario and McMaster Universities Osteoarthritis Index, 20-m fast-paced walk test, 30-second chair-stand test, stair-climb test, timed up and go test, and single leg stance. Cardiorespiratory fitness, strength, and body composition were evaluated using peak oxygen consumption (VO2 peak), isometric knee extensor/flexor strength, and dual-energy x-ray absorptiometry, respectively. HIIT was completed two times/week (cycling or treadmill) and consisted of 10 repetitions of 1-minute bouts at 90% VO2 peak, with 1-minute rest periods. Separate multivariable-adjusted linear mixed models were fit for each outcome with fixed effects of time, age, sex, body mass index, and random effects of baseline values to estimate mean changes and 95% confidence intervals (CIs) between baseline and 12-week assessments.

RESULTS

Recruitment aligned with the anticipated enrollment rate, adherence was 70%, and no adverse events were reported. At 12 weeks, improvements were observed for most outcomes, with notable mean changes for the 20-m fast-paced walk (-1.13 [95% CI -1.61 to -0.64] seconds), 30-second chair-stand (2.6 [1.8-3.4] stands), and VO2 peak (0.14 [0.03-0.24] liters/minute).

CONCLUSION

In this 12-week pilot study, HIIT improved multiple aspects of health in individuals with knee OA; larger studies are needed.

Sociodemographic and Clinical Predictors of Prescription Opioid Use in a Longitudinal Community-Based Cohort Study of Middle-Aged and Older Adults

Objectives

Identifying factors associated with opioid use in middle-aged and older adults is a fundamental step in the mitigation of potentially unnecessary opioid consumption and opioid-related harms.

Methods

Using longitudinal data on a community-based cohort of adults aged 50–90 years residing in Johnston County, North Carolina, we examined sociodemographic and clinical factors in non-opioid users (n = 786) at baseline (2006–2010) as predictors of opioid use at follow-up (2013–2015). Variables included age, sex, race, obesity, educational attainment, employment status, household poverty rate, marital status, depressive symptoms, social support, pain catastrophizing, pain sensitivity, insurance status, polypharmacy, and smoking status.

Results

At follow-up, 13% of participants were using prescription opioids. In the multivariable model, high pain catastrophizing (adjusted odds ratio; 95% confidence interval = 2.14; 1.33–3.46), polypharmacy (2.08; 1.23–3.53), and history of depressive symptoms (2.00; 1.19–3.38) were independent markers of opioid use.

Discussion

Findings support the assessment of these modifiable factors during clinical encounters in patients ≥ 50 years old with chronic pain.

The Prevalence of Knee Symptoms, Radiographic, and Symptomatic Osteoarthritis at Four Time Points: The Johnston County Osteoarthritis Project, 1999-2018

Objective

To describe point prevalence of knee symptoms, radiographic knee osteoarthritis (rKOA), severe rKOA, and symptomatic rKOA at four time points in the longitudinal, population‐based Johnston County Osteoarthritis Project (JoCo OA).

Methods

Data were from 2573 JoCo OA participants with up to 18 years of follow‐up (1999‐2018) and standardized fixed‐flexion knee radiographs read by a single, reliable expert musculoskeletal radiologist. The four outcomes were 1) self‐reported knee symptoms, defined by “On most days, do you have pain, aching, or stiffness in your right/left knee?”; 2) rKOA, defined as a Kellgren‐Lawrence grade (KLG) of 2 to 4); 3) severe rKOA, defined as a KLG of 3 or 4; and 4) symptomatic rKOA, defined as both symptoms and rKOA in the same joint. Weighted prevalence estimates and 95% confidence intervals (CIs) were generated overall and by age group, sex, race, and body mass index (BMI).

Results

Most recently (2017‐2018, T4), the overall prevalence (percentage) of knee symptoms, rKOA, severe rKOA, and symptomatic rKOA was 41% (95% CI: 35‐47%), 61% (95% CI: 56‐67%), 35% (95% CI: 30‐40%), and 30% (95% CI: 24‐35%), respectively. From time point T1 to T4, prevalence increased for rKOA, severe rKOA, and symptomatic rKOA but not for knee symptoms. The prevalence of both severe rKOA (17‐39%) and symptomatic rKOA (23‐30%) was consistently higher among women. The prevalence of all outcomes was higher among those with higher BMI and among Black participants at all time points, particularly rKOA (35‐69%) and severe rKOA (22‐46%).

Conclusion

These updated estimates demonstrate a large and increasing burden of knee OA, particularly among women and Black individuals.

Associations of Comorbid Conditions and Transitions Across States of Knee Osteoarthritis in a Community-Based Cohort

OBJECTIVE

To examine relationships between knee osteoarthritis (KOA) and obesity, diabetes mellitus (DM), and cardiovascular disease (CVD).

METHODS

Associations of time-dependent obesity, DM, and CVD with KOA transition states over approximately 18 years were examined among 4093 participants from a community-based cohort. Transition states were 1) no knee symptoms and no radiographic KOA (rKOA; Kellgren-Lawrence grade ≥2 in at least one knee), 2) asymptomatic rKOA, 3) knee symptoms only, 4) symptomatic rKOA (sxKOA; rKOA and symptoms in same knee). Markov multistate models estimated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for associations between comorbid conditions and transitions across states, adjusting for baseline age, sex, race, education, enrollment cohort, birth year, and time-dependent knee injury history.

RESULTS

At baseline, 40% of participants had obesity, 13% had DM, and 22% had CVD (mean age = 61 years; 34% Black; 37% male). Compared with those without obesity, those with obesity had a higher hazard of worsening from no rKOA/no symptoms to asymptomatic rKOA (aHR = 1.7; 95% CI = 1.3-2.2) and from knee symptoms to sxKOA (aHR = 1.7; 95% CI = 1.3-2.3), as well as a lower hazard of symptom resolution from sxKOA to asymptomatic rKOA (aHR = 0.5 [95% = CI 0.4-0.7]). Compared with those without CVD, those with CVD had a higher hazard of worsening from no rKOA/symptoms to knee symptoms (aHR = 1.5; 95% CI = 1.1-2.1). DM was not associated with transitions of rKOA.

CONCLUSION

Prevention of obesity and CVD may limit the development or worsening of rKOA and symptoms.

Statistical shape modeling of the hip and the association with hip osteoarthritis: a systematic review

OBJECTIVE

To summarize available evidence on the association between hip shape as quantified by statistical shape modeling (SSM) and the incidence or progression of hip osteoarthritis.

DESIGN

We conducted a systematic search of five electronic databases, based on a registered protocol (available: PROSPERO CRD42020145411). Articles presenting original data on the longitudinal relationship between radiographic hip shape (quantified by SSM) and hip OA were eligible. Quantitative meta-analysis was precluded because of the use of different SSM models across studies. We used the Newcastle-Ottawa Scale (NOS) for risk of bias assessment.

RESULTS

Nine studies (6,483 hips analyzed with SSM) were included in this review. The SSM models used to describe hip shape ranged from 16 points on the femoral head to 85 points on the proximal femur and hemipelvis. Multiple hip shape features and combinations thereof were associated with incident or progressive hip OA. Shape variants that seemed to be consistently associated with hip OA across studies were acetabular dysplasia, cam morphology, and deviations in acetabular version (either excessive anteversion or retroversion).

CONCLUSIONS

Various radiographic, SSM-defined hip shape features are associated with hip OA. Some hip shape features only seem to increase the risk for hip OA when combined together. The heterogeneity of the used SSM models across studies precludes the estimation of pooled effect sizes. Further studies using the same SSM model and definition of hip OA are needed to allow for the comparison of outcomes across studies, and to validate the found associations.

Precision Medicine Approach to Develop and Internally Validate Optimal Exercise and Weight-Loss Treatments for Overweight and Obese Adults With Knee Osteoarthritis: Data From a Single-Center Randomized Trial

OBJECTIVE

To apply a precision medicine approach to determine the optimal treatment regime for participants in an exercise (E), dietary weight loss (D), and D + E trial for knee osteoarthritis that would maximize their expected outcomes.

METHODS

Using data from 343 participants of the Intensive Diet and Exercise for Arthritis (IDEA) trial, we applied 24 machine-learning models to develop individualized treatment rules on 7 outcomes: Short Form 36 physical component score, weight loss, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain/function/stiffness scores, compressive force, and interleukin-6 level. The optimal model was selected based on jackknife value function estimates that indicate improvement in the outcomes if future participants follow the estimated decision rule compared to the optimal single, fixed treatment model.

RESULTS

Multiple outcome random forest was the optimal model for the WOMAC outcomes. For the other outcomes, list-based models were optimal. For example, the estimated optimal decision rule for weight loss indicated assigning the D + E intervention to participants with baseline weight not exceeding 109.35 kg and waist circumference above 90.25 cm, and assigning D to all other participants except those with a history of a heart attack. If applied to future participants, the optimal rule for weight loss is estimated to increase average weight loss to 11.2 kg at 18 months, contrasted with 9.8 kg if all participants received D + E (P = 0.01).

CONCLUSION

The precision medicine models supported the overall findings from IDEA that the D + E intervention was optimal for most participants, but there was evidence that a subgroup of participants would likely benefit more from diet alone for 2 outcomes.

Hip symptoms are associated with premature mortality: the Johnston County Osteoarthritis Project

OBJECTIVE

To investigate the impact of hip osteoarthritis (OA) and/or hip symptoms on excess mortality.

DESIGN

We analyzed data from 3,919 individuals in a community-based prospective cohort of African Americans and Caucasians age ≥45 years. Women ≥50 years of age and all men underwent supine anteroposterior pelvic radiography at baseline, with the participant's feet in 15 degrees of internal rotation. Hip radiographic (rOA) was defined as a Kellgren-Lawrence grade of ≥2 in at least one hip. Participants completed questionnaires at baseline to determine presence of hip symptoms and covariate status. Participants with symptomatic hip rOA (SxOA) are a subset of individuals with hip rOA and symptoms in the same hip. Multiple imputation was used to impute missing values of covariates. Mortality was determined through 2015 and follow-up time was calculated from baseline assessment until death or censoring which took place when a participant was lost to follow-up or reached the end of study period. Cox proportional hazards regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI). We carried out additional analyses stratified by sex, race, age and obesity.

RESULTS

Mean follow-up time was 14.2 years during which 1762 deaths occurred. There were 29.9% participants in our population with hip rOA at baseline. Compared to those with neither hip rOA nor hip symptoms, we observed an increased risk of all-cause mortality in participants with hip symptoms alone (HR = 1.28, 95% CI = 1.13-1.46), but no association for hip rOA either with or without symptoms. In stratified analyses we observed increased associations for hip symptoms alone and hip sxOA in those <65 years (43% and 39% increase, respectively) and in Caucasians (34% and 21% increase, respectively).

CONCLUSIONS

Individuals who had hip symptoms without hip rOA had an increased risk of mortality. These effects were particularly strong for those who were <65 years of age and Caucasians. Effective interventions to identify those with hip pain in order to lessen it could reduce premature mortality.

Turning the Page in Osteoarthritis Assessment with the Use of Ultrasound

PURPOSE OF REVIEW

This narrative review summarizes the last 5 years of published, peer-reviewed research on the use of musculoskeletal ultrasound (US) in osteoarthritis (OA).

RECENT FINDINGS

Multiple features relevant to OA can be visualized on US, including synovitis, erosion, enthesitis, osteophytes, cartilage damage, meniscal extrusion, and popliteal cysts. US can be used to confirm a diagnosis of OA or make an alternate diagnosis in the clinical setting. When a standardized protocol is used, US is a reliable modality for assessment of the features of OA. Findings on US can predict progression and response to therapy in OA of the hand and knee and can allow characterization of risk factors in a cost-effective, non-invasive, repeatable manner. US is becoming more widely used in OA imaging and has clear value in addition to radiography and clinical assessment. US will likely prove useful in defining phenotypes and providing treatment guidance in OA.

Foot Osteoarthritis Frequency and Associated Factors in a Community-Based Cross-Sectional Study of White and African American Adults

OBJECTIVE

Few studies have explored foot osteoarthritis (OA) in the general population. The purpose of this study was to determine the frequency of foot OA and identify associated factors in a cross-sectional analysis of a large community-based cohort.

METHODS

Data were from the 2013-2015 study visit of the Johnston County OA Project. Radiographic OA of the foot was defined using the La Trobe radiographic atlas (≥2 osteophytes or joint space narrowing in at least 1 of 5 joints). Symptomatic OA of the foot was defined as foot radiographic OA with pain, aching, or stiffness in the same foot. At the foot-level, separate logistic regression models with generalized estimating equations to account for intraperson correlations were performed to examine associations of foot radiographic OA or symptomatic OA with age, body mass index (BMI), sex, race, educational attainment, and previous foot injury.

RESULTS

Of 864 participants with available data (mean age 71 years, mean BMI 30 kg/m² , 68% women, 33% African American, 13% <12 years of schooling), 22% had foot radiographic OA, 20% had foot symptoms, and 5% had foot symptomatic OA. Radiographic, but not symptomatic, foot OA was more common in African American than White participants. Participants with obesity, compared to normal weight, had >2 times the odds of radiographic OA and >5 times the odds of symptomatic OA in adjusted models.

CONCLUSION

Foot radiographic OA and foot symptoms were common in the sample, but both conditions simultaneously (i.e., symptomatic OA) occurred infrequently. Notably, obesity was linked with foot symptomatic OA, perhaps implicating metabolic or mechanical influences.

A Standardized, Pragmatic Approach to Knee Ultrasound for Clinical Research in Osteoarthritis: The Johnston County Osteoarthritis Project

Objective

This study sought to develop and employ a comprehensive and standardized ultrasound (US) protocol and scoring atlas for the evaluation of features relevant to knee osteoarthritis (KOA) in a community‐based cohort in the United States, with the goals of demonstrating feasibility, reliability, and validity.

Methods

We utilized data from the fourth follow‐up (2016‐2018) of the Johnston County OA Project, which includes individuals with (~50%) and without radiographic KOA. All participants underwent standardized knee radiography and completed standard questionnaires including the Knee Injury and Osteoarthritis Outcome Score (KOOS). Bilateral knee US images were obtained by a trained sonographer using a standardized protocol and scored by trained rheumatologists using an atlas developed for this study. A total of 396 knees were each scored by two readers according to the atlas. Associations between US features, radiographic findings (graded by an expert radiologist), and KOOS scores were assessed.

Results

Overall interreader reliability for US scoring was fair to moderate. The strongest correlations between US and radiographic features were seen for osteophytes, and similarly strong correlations were seen between US osteophytes and overall radiographic Kellgren‐Lawrence Grade, demonstrating criterion validity. Features of effusion/synovitis and osteophytes were most associated with KOOS pain and impaired function.

Conclusion

US is a feasible, reliable, and valid method to assess features relevant to KOA in clinical and research settings. The protocol and atlas developed in this study can be utilized to evaluate KOA in a standardized fashion in future clinical studies, enabling greater utilization of this valuable modality in osteoarthritis.

Osteoarthritis physical activity care pathway (OA-PCP): results of a feasibility trial

BACKGROUND

To obtain information on feasibility and acceptability, as well as preliminary data on efficacy, of an Osteoarthritis Physical activity Care Pathway (OA-PCP).

METHODS

This was a single group pilot study involving 60 participants with symptomatic, physician diagnosed knee or hip OA, recruited from primary care clinics. Participants self-reported completing less than 150 min per week of moderate-to-vigorous physical activity (MVPA) at baseline. The 3-month OA-PCP intervention involved 3 physical activity (PA) coaching calls (focused on goal setting), three check-in emails and linkage with community-based or online resources to support PA. Efficacy outcomes were collected at baseline and 4-month follow-up. The primary efficacy outcome was minutes of MVPA, assessed via accelerometer. Secondary outcomes included minutes of light intensity activity, sedentary minutes, step counts, and Western Ontario and McMaster Universities (WOMAC) pain and function subscales. Participants were also asked to rate the helpfulness of the OA-PCP intervention on a scale of 0-10. Differences in efficacy outcomes between baseline and 4-month follow-up were assessed using paired t-tests.

RESULTS

Among participants beginning the study, 88% completed follow-up assessments and ≥ 90% completed each of the intervention calls. Average daily minutes of MVPA was 8.0 at baseline (standard deviation (SD) = 9.9) and 8.9 at follow-up (SD = 12.1, p = 0.515). There were no statistically significant changes in light intensity activity, sedentary time or step counts. The mean WOMAC pain score improved from 8.1 (SD = 3.6) at baseline to 6.2 (SD = 3.8) at follow-up (p < 0.001); the mean WOMAC function score improved from 26.2 (SD = 13.2) to 20.2 (SD = 12.5; p < 0.001). The mean rating of helpfulness was 7.6 (SD = 2.5).

CONCLUSIONS

Results supported the feasibility and acceptability of the study, and participants reported clinically relevant improvements in pain and function. PA metrics did not improve substantially. Based on these results and participant feedback, modifications including enhanced self-monitoring are being made to increase the impact of the OA-PCP intervention on PA behavior.

TRIAL REGISTRATION

NCT03780400, December 19, 2018.

Application of Traditional and Emerging Methods for the Joint Analysis of Repeated Measurements With Time-to-Event Outcomes in Rheumatology

OBJECTIVE

The goal of this paper is to describe approaches for the joint analysis of repeatedly measured data with time-to-event end points, first separately and then in the framework of a single comprehensive model, emphasizing the efficiency of the latter approach. Data from the Johnston County Osteoarthritis (JoCo OA) Project will be used as an example to investigate the relationship between the change in repeatedly measured body mass index (BMI) and the time-to-event end point of incident worsening of radiographic knee OA that was defined as an increased Kellgren/Lawrence grade in at least 1 knee over time.

METHODS

First, we provide an overview of the methods for analyzing repeated measurements and time-to-event end points separately. Then, we describe traditional (Cox proportional hazards model [CoxPH]) and emerging (joint model [JM]) approaches, both of which allow combined analysis of repeated measures with a time-to-event end point in the framework of a single statistical model. Finally, we apply the models to JoCo OA data and interpret and compare the results from the different approaches.

RESULTS

Applications of the JM (but not the CoxPH) showed that the risk of worsening radiographic OA is higher when BMI is higher or increasing, thus illustrating the advantages of the JM for analyzing such dynamic measures in a longitudinal study.

CONCLUSION

Joint models are preferable for simultaneous analyses of repeated measurement and time-to-event outcomes, particularly in the context of chronic disease, where dependency between the time-to-event end point and the longitudinal trajectory of repeated measurements is inherent.

Incidence and progression of hand osteoarthritis in a large community-based cohort: the Johnston County Osteoarthritis Project

OBJECTIVE

To describe the incidence and progression of radiographic and symptomatic hand osteoarthritis (rHOA and sxHOA) in a large community-based cohort.

DESIGN

Data were from the Johnston County OA Project (1999-2015, 12 ± 1.2 years follow-up, age 45+). Participants had bilateral hand radiographs each visit, read for Kellgren-Lawrence grade (KLG) at 30 joints. We defined rHOA as KLG ≥2 in ≥1 joint. SxHOA was defined in a hand/joint with rHOA and self-reported symptoms or tenderness on exam. Incidence was assessed in those without, while progression was assessed in those with, baseline rHOA. Proportions or medians are reported; differences by sex and race were assessed using models appropriate for dichotomous or continuous definitions, additionally adjusted for age, education, body mass index (BMI), and weight change.

RESULTS

Of 800 participants (68% women, 32% African American, mean age 60 years), 327 had baseline rHOA and were older, more often white and female, than those without rHOA (n = 473). The incidence of HOA was high, for rHOA (60%) and for sxHOA (13%). Women were more likely than men to have incident HOA, particularly for distal interphalangeal joint radiographic osteoarthritis (DIP rOA) (adjusted odds ratios (aOR) 1.60 95% confidence intervals (95% CI) [1.03, 2.49]) and sxHOA (aOR 2.98 [1.50, 5.91]). Progressive HOA was more similar by sex, although thumb base rOA progressed more frequently in women than in men (aOR 2.56 [1.44, 4.55]). Particularly HOA incidence, but also progression, was more frequent among whites compared with African Americans.

CONCLUSION

This study provides much needed information about the natural history of HOA, a common and frequently debilitating condition, in the general population.